Automated Test Equipment Temperature Control via Fitting Approach
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing automated test equipment struggles to effectively control the temperature of devices under test during testing, leading to potential yield loss and thermal excursions, while also being user-friendly, computationally efficient, and requiring minimal implementation effort.
Innovation Solution
The automated test equipment analyzes a testing profile to determine information describing temperature peaks using a fitting approach, and then generates temperature control instructions to manage these peaks, thereby maintaining optimal testing conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If temperature control is implemented during testing, then temperature stability is improved, but device complexity increases
Solution Approach 1:
The system automatically analyzes testing profiles to identify temperature peaks and generates control instructions without requiring manual intervention. The automated test equipment performs self-service temperature control by autonomously determining when and how to adjust temperatures based on observed thermal behavior during testing.
Solution Approach 2:
The system dynamically adjusts temperature control parameters based on the analyzed testing profile. By changing temperature setpoints and control timing according to identified thermal peaks, the system achieves adaptive temperature stability without requiring complex fixed control mechanisms.
2Reliability
If automated temperature control is implemented, then temperature control reliability is improved, but computational complexity increases
Solution Approach 1:
The system extracts only the critical temperature peak information from the complete testing profile using fitting approaches. By focusing computational resources on identifying and controlling significant thermal events rather than processing the entire temperature curve, the system achieves reliable temperature control with reduced computational burden.
Solution Approach 2:
The system uses fitting functions to create simplified mathematical representations of temperature peaks. These fitted models serve as computational copies that capture the essential thermal behavior without requiring complex real-time processing of raw temperature data, thereby improving reliability while reducing computational complexity.
3Manufacturing precision
If detailed temperature profile analysis is performed, then temperature control precision is improved, but implementation effort increases
Solution Approach 1:
The automated test equipment autonomously performs the complete temperature profile analysis and control instruction generation without requiring manual implementation. The system self-services the complex analytical tasks by automatically fitting temperature data, identifying peaks, and determining control parameters, thereby achieving high precision with minimal user effort.
Solution Approach 2:
The system replaces manual analysis and control setup with automated computational methods. By using algorithmic fitting approaches and automatic control instruction generation, the system achieves detailed temperature control precision without requiring manual implementation of complex analytical procedures.
Data Source
AI summary
An automated test equipment, ATE, for testing a device under test, DUT, is configured to obtain a testing profile indicating an evolution of a DUT temperature during an execution of a given test flow. The automated test equipment is configured to analyze the testing profile, in order determine an information describing a plurality of temperature peaks using a fitting approach. The automated test equipment is configured to obtain a plurality of temperature control instructions for an execution of a test flow on the basis of the information describing the plurality of temperature peaks.